Beyond “Couch Potatoes”: From Consumers to Designers and ...l3d.cs.colorado.edu/~gerhard/papers/couchpotato-firstmonday.pdfcontributes to the degeneration of humans into “couch

Gerhard Fischer 1 FirstMonday Submission

Beyond “Couch Potatoes”: From Consumers to Designers andActive Contributors

Gerhard FischerUniversity of Colorado, Center for LifeLong Learning and Design (L3D)

Department of Computer Science, Campus Box 430Boulder, CO 80309-0430 - USA

[email protected]

AbstractThe fundamental challenge for computational media is to contribute to the invention and design of cultures inwhich humans can express themselves and engage in personally meaningful activities. Cultures aresubstantially defined by their media and tools for thinking, working, learning, and collaborating. Newmedia change (1) the structure and contents of our interests, (2) the nature of our cognitive and collaborativetools, and (3) the social environment in which thoughts originate and evolve, and mindsets develop.Unfortunately, a large number of new media are designed from a perspective of seeing and treating humansprimarily as consumers. In personally meaning and important activities, the possibility for humans to be andto act as designers (in cases in which they desire to do so) should be accessible not only to a small group of“high-tech scribes,” but rather to all interested individuals and groups. While the core message of thearticle applies to cultures, mindsets, media, technologies, and educational systems in general, my examplesare mostly drawn from computational media, and more specifically from human computer interaction as aparticular domain.

Keywords:consumer; designer; personal meaningful activities; active contributor; mindsets; informed participation;meta-design; design time and use time; seeding, evolutionary growth, reseeding model; unselfconsciouscultures of design; high-tech scribes; division of labor; social creativity; social capital; computationalenvironments supporting active contributors; domain-oriented design environments; Envisionment andDiscovery Collaboratory; living computational memories


Table of Contents

1 Introduction ...................................................................................................................................... 42 Images of Humans............................................................................................................................ 5

2.1 A Consumer Perspective ............................................................................................................. 52.2 A Designer Perspective................................................................................................................ 52.3 Beyond Binary Choices ............................................................................................................... 6

3 Implications of a Designer Perspective............................................................................................. 83.1 Informed Participation ................................................................................................................ 83.2 Meta-Design................................................................................................................................. 93.3 The Seeding, Evolutionary Growth, and Reseeding Model....................................................... 11

4 Technology and Media Support for Designer Roles ..................................................................... 134.1 Domain-Oriented Design Environments.................................................................................... 134.2 Envisionment and Discovery Collaboratory ............................................................................. 154.3 Living Computational Memories............................................................................................... 17

5 The Ubiquity of the Consumer / Designer Spectrum..................................................................... 185.1 Architecture............................................................................................................................... 195.2 Open Source: A Success Model of Collaborative Design in a Designer Culture ....................... 195.3 Learning and Education............................................................................................................ 20

6 Assessment ...................................................................................................................................... 216.1 Technology Assessment ............................................................................................................. 226.2 Utility = Value / Effort................................................................................................................ 226.3 Social Capital ............................................................................................................................ 236.4 Trade-offs in a “Do-It-Yourself Society”................................................................................... 246.5 Mindsets..................................................................................................................................... 246.6 Cross-Cultural Perspectives....................................................................................................... 25

7 Conclusions..................................................................................................................................... 258 Acknowledgments............................................................................................................................ 269 References ....................................................................................................................................... 26


List of Figures

Figure 1: Children Creating their Own Jewelry ____________________________________________________________4Figure 2: Beyond Binary Choices — The Consumer/Designer Spectrum ________________________________________7Figure 3: Duality between Learning and Contributing_______________________________________________________9Figure 4: Design and Use Time _______________________________________________________________________10Figure 5: The Seeding, Evolutionary Growth, Reseeding Process Model _______________________________________11Figure 6: Technology and Media Support for Consumer and Designer Roles____________________________________13Figure 7: A Domain-Oriented Design Environment for Computer Network Design_______________________________14Figure 8: A Layered Architecture Supporting Human Problem Domain Interaction_______________________________15Figure 9: The Envisionment and Discovery Collaboratory __________________________________________________16Figure 10: The Participate-in-the-Action (PiTa Board)______________________________________________________17

List of Tables

Table 1: Comparing Consumer and Designer Roles ________________________________________________________7Table 2: Traditional versus New Models of Working and Learning in Organizations ______________________________21


1 IntroductionCultures are substantially defined by their media and their tools for thinking, working, learning, andcollaborating. A large number of the new media are designed to see humans only as consumers. Television isthe most obvious medium that promotes this mindset and behavior [Fischer, 1999; Postman, 1985] andcontributes to the degeneration of humans into “couch potatoes,” for whom a remote control is the mostimportant instrument of their cognitive activities (a “couch potato” is a colloquial expression for a personwho spends a lot of time on a couch consuming food and information in a passive fashion and who rarelyengages in intellectual or physical activities).A consumer mindset is not limited to television. In our educational institutions learners are often treated asconsumers, creating a mindset of consumerism for the rest of their lives [Illich, 1971]. Citizens often feel leftout of the decisions by policy makers, denying them opportunities to take an active role. Computationalmedia have the unique potential to let people be designers or assist them to gradually become designers.Unfortunately, most current computational environments do not allow users to act as contributors anddesigners.

Figure 1: Children Creating their Own Jewelry

The basic idea of the paper is illustrated in Figure 1: rather than buying jewelry as a finished product, thesechildren create their own jewelry — they act as designers. The store supports this process by providing a great


variety of basic materials, tools, and a social setting including space and a human coach or facilitator to helpthe children.The concept “designer” in the context of this paper is used very broadly for a person who wants to act as anactive participant and contributor in personally meaningful activities. In this paper I will: (1) differentiatebetween consumer and designer perspectives; (2) discuss media support or limitations for these roles; (3)describe innovative computational media from this perspective and illustrate them with examples from ourwork (for more information see: http://www.cs.colorado.edu/~l3d/ ); and (4) provide some evidence for theubiquity of this framework in our society.

2 Images of HumansDepending on work, learning, and leisure activities, different people will consider different activities aspersonally meaningful and important. In today’s world with more information available and delivered in ourhomes, classrooms, and entertainment centers, a consumer perspective is well supported, and can easily andcompletely fill our lives thereby reducing “doing” activities even more in favor of “watching” activities.

2.1 A Consumer PerspectiveThe Director of Research for Time Warner Entertainment, in his closing plenary address at the ComputerHuman Interaction (CHI’95) 1995 conference, argued that the design of a remote control to browse andefficiently select 500 or more TV channels as the basic challenge for the human computer interaction (HCI)research community. Without a doubt, solving this problem is of great commercial interest to industries tha tregard humans as the pure consumers (meaning consumption is their highest priority or most importantactivity—but is it, or should it be, a focal issue for HCI?In the early days of computing, humans were considered the “servants” of computers. As computers becamecheaper, the basic economic criteria started to change and considerations of how to use computational powerto augment and empower human beings were pioneered by some early visionaries [Engelbart & English, 1968;Kay, 1984]. These new ideas were neither known nor embraced by the community at large. The ArtificialIntelligence community developed expert systems (such as MYCIN [Buchanan & Shortliffe, 1984]), whichwere behaviorally unacceptable because they restricted knowledgeable and skilled human professionals to aconsumer role by allowing them only to answer “yes” or “no” to questions generated by the system. Otherdisciplines such as human factors [Norman, 1988] often considered humans as system components with specificcharacteristics such as limited attention span, faulty memory, and easy distractibility along with other“undesirable” characteristics.

2.2 A Designer PerspectiveEarly research in HCI focused on novices and naive users, and how walk-up-and-use systems could supporttheir needs. Little consideration in the first decade of HCI research was given to the following perspectives:• to support domain designers (being skilled and knowledgeable in specific domains) who are neither

novices nor naive users, but who are interested in their work and who see the computer as a means ratherthan as an end [Henderson & Kyng, 1991; Nardi, 1993];

• to create co-adaptive environments, in which users change, because they learn, and in which systemschange, because users have the ability to adapt systems to better suit their practices [Mackay, 1990];

• how to create intrinsically motivating computational environments [Csikszentmihalyi, 1990], in whichusers of all backgrounds would feel in control, and could engage in activities which they would findinteresting, challenging, rewarding, and matched to their needs and interests; and

• how to design media for collaborative design, and in particular media to support design communities tocreate, share and manage knowledge [Fischer & Ostwald, 2001].


The HCI community slowly started to understand that (at least) some humans wanted to be more thanconsumers, and were not content with being novices or naive users indefinitely. New design philosophiesintroduced important new research objectives such as user-centered design [Norman & Draper, 1986], learner-centered design [Communications of the ACM, 1996], and human-centered design [Flanagan et al., 1997]. Somemembers of the AI community started to consider the true goal of AI not as the replacement of human beings,but as the empowerment and augmentation of humans [Fischer & Nakakoji, 1992; Terveen, 1995].My arguments in this paper rest on the fundamental belief that humans (not all of them, not at all times, notin all contexts) want to be and act as designers in personally meaningful activities requiring convivial toolswhich are defined as follows [Illich, 1973]: “convivial tools allow users to invest the world with t h e i rmeaning, to enrich the environment with the fruits of their vision and to use them for the accomplishment o fa purpose they have chosen”. Convivial tools encourage users to be actively engaged in generating creativeextensions to the artifacts given to them and have the potential to break down the strict counterproductivebarriers between consumers and designers [Brown & Duguid, 2000].Many computer users and designers today are domain professionals, competent practitioners, anddiscretionary users and should not be considered naïve users, or dummies (despite the infinite number of booksentitled “X for Dummies”). They worry about tasks, they are motivated to contribute and to create goodproducts, they care about personal growth, and they want to have convivial tools that make themindependent of “high-tech scribes” (whose role is defined by the fact that the world of computing is still toomuch separated into a population of elite scribes who can act as designers and a much larger population ofintellectually disenfranchised computer phobes who are forced into a consumer role). The experience ofhaving participated in the framing and solving of a problem or in the creation of an artifact (see Figure 1)makes a difference to those who are affected by the solution and therefore consider it personally meaningfuland important: “people are more likely to like a solution if they have been involved in its generation; eventhough it might not make sense otherwise” [Rittel, 1984].A fundamental challenge for the next generation of computational media and new technologies is not todeliver predigested information to individuals, but to provide the opportunity and resources for socialdebate, discussion, and collaborative design. In many design activities, learning cannot be restricted to findingknowledge that is “out there.” For most design problems (ranging from urban design to graphics design andsoftware design that we have studied over many years), the knowledge to understand, frame, and solveproblems does not exist; rather it is constructed and evolved during the process of solving these problems,exploiting the power of the “symmetry of ignorance” [Rittel, 1984] and “breakdowns” [Fischer, 1994; Schön,1983]. From this perspective, access to existing information and knowledge (often seen as the major advance ofnew media) is a very limiting concept [Arias et al., 1999; Brown et al., 1994; PCAST, 1997] and should becomplemented by creating opportunities for people to engage in informed participation (see section 3.1 and[Arias et al., 1999]).

2.3 Beyond Binary ChoicesBy arguing for the desirability of humans to be designers, I want to state explicitly that there is nothingwrong with being a consumer and that we can learn and enjoy many things in a consumer role (e.g., listening toa lecture, watching a tennis match, attending a concert, seeing things in a movie on our couch that we areunable to see first hand). I also do not assume that being a consumer or being a designer would be a binarychoice: it is rather a continuum [Repenning et al., 1999] ranging from passive consumer, to active consumer, toend-user, to user, to power users, to domain designer, all the way to meta-designer (see Figure 2). It is also thecase that the same person is and wants to be a consumer in some situations and in others a designer; therefore“consumer / designer” is not an attribute of a person, but of a context. Good designers should be well-informedconsumers (e.g., they should exploit reuse as a powerful design strategy by “consuming” existing information,and exploit the contributions of the “giants” who preceded them).


Consumer <--------------------------------------------------------------------->Designer

passive consumeractive consumer end-user

user power users, local developers domain designer meta-designer

Figure 2: Beyond Binary Choices — The Consumer/Designer Spectrum

In thinking about the role of new media and new technologies for the future, the consumer asks: “Is a newfuture coming?” whereas the designer asks: “How can we invent and create a new future?” The designerunderstands that the future is not out there to be “discovered”(like Columbus discovered America) —but i thas to be invented and designed. Accepting this will raise the issue: who will design the future? I claim that(1) social scientists (interested in understanding new media) should not be content with either assessing orevaluating new media which others have designed, and that (2) the HCI community should not restrict itsefforts to user interfaces or the computer part of HCI confining itself to focus solely on some technical issues inthe context of a world defined by others.Based on the great benefits derived from the division of labor [Campbell, 1969; Florida, 2002] professionaldesigners play an important role in our society. The “average” person does not want to build her/his ownhouse, design her/his own car, or write her/his own software system or sorting routine, and therefore is gladto delegate such tasks to domain designers. Likewise, most people do not have the time to participate equallyin all aspects of the political system in order to become fully engaged and informed, and therefore rely onintermediaries who act in their interests.The situation is only problematic when

(1) someone wants to be a designer in personally meaningful activities but is forced to be a consumer; and(2) someone wants to be a consumer in personally irrelevant activities but is forced to be a designer.

Table 1: Comparing Consumer and Designer Roles

consumer designeractivity use, listen, surf;

access existing information; acquireprerequisites for engaging in designactivities

modify, create, make your own waves;informed participation

learning effort small largedepth of understanding shallow deepengagement normal substantiallearning opportunities limited because no artifacts are

createdthe “back-talk” and the “breakdowns” fromthe artifacts created lead to learningopportunities

mismatch wanting to be a designer inpersonally relevant activities

wanting to be a consumer in personallyirrelevant activities

rewards pleasure develop new skills, peer recognition, socialcapital


For example: I personally prefer to be a consumer with respect to technology that I use only occasionally suchas cellular phones, car radios, VCRs, and voice mail. Each of these systems comes with hundreds of pages ofdocumentation, including extensive customization features and for which I do not have the interest nor thetime to understand, learn, and remember. My interest to act as designer is very different for core technologiesthat I use on a daily basis for personally meaningful and important tasks such as writing papers, developingpresentations, and communicating with others. Table 1 summarizes consumer and designer roles according tosome of the criteria discussed.A critical challenge addressed by our research is to support a migration path [Burton et al., 1984] between thedifferent roles mentioned in Figure 2: consumers, power-users, and designers are nurtured and educated, notborn, and people must be supported to assume these roles. This is a social as well a technical challenge tha tunderlies many of the core ideas of this paper.

3 Implications of a Designer PerspectiveWhereas computer scientists find computers intrinsically interesting and like computers because they get toprogram, skilled domain workers regard computers as useful, sometimes even indispensable machines capableof helping them work on their problems more productively, creatively, and with greater pleasure [Landauer,1995; Nardi, 1993]. Skilled domain workers are not novices or naive users, particularly with respect to domainconcepts. They are people who have computational needs, who want and need to be designers in personallymeaningful tasks. They make serious use of computers in their work, but they are not interested in becomingprofessional computer scientists.They are skilled and knowledgeable in their respective domains; they use computers by choice and overextended periods of time. To understand their use of computers requires a new orientation for many current HCIefforts. Rather than focusing exclusively on short-term, tool-oriented events HCI must also investigateactivities that extend over days, months, and years such as educational, social, and organizational needs[Carroll, 1993]. Traditional HCI efforts have focused on evaluating the user interface aspects of tools, ratherthan their applicability to the problem domain.

3.1 Informed Participation“If you don't participate, then your voice won't be heard”

— a participant in a planning session of a neighborhood transportation system

Informed participation is a form of collaborative design in which participants from all walks of life—not justskilled computer professionals—are empowered to incrementally acquire ownership in problems and tocontribute actively to their solutions [Brown et al., 1994; Fischer & Ostwald, 2002]. Informed participationattempts to address the open-ended and multidisciplinary design problems that are most pressing in oursociety. These problems, which typically involve a combination of social and technological issues[Greenbaum & Kyng, 1991], do not have “right” answers, and the knowledge to understand and resolve themchanges rapidly, thus requiring an ongoing and evolutionary approach to problem solving.Informed participation involves communities of interest [Fischer, 2001] made up of people from differentcommunities of practice [Wenger, 1998], each having a unique stake in a common problem. Stakeholders areengaged in both learning and contributing activities. New knowledge is constructed when learning andcontributing feed each other, ultimately producing a greater shared understanding than could be achieved byeach of the participants on their own [Resnick et al., 1991].Informed participation emphasizes mutual learning for sharing the unique knowledge that each stakeholderbrings to a design problem, and evolution-based design approaches, in which problem framing and problemsolving are intertwined [Schön, 1983]. Another key emphasis of informed participation is to leverage priorand related design efforts as a source of problem-solving knowledge. While no two problems are exactly thesame, similar problems can provide valuable insights that help to understand the problem at hand.Informed participation is impossible in communities in which most of the members regard themselves asconsumers. Individuals within communities must be encouraged to evolve into power-users [Nardi, 1993] who


not only use artifacts and information, but also modify and extend them [Mackay, 1990]. Individuals (actingas designers) must acquire a new mindset—they are no longer passive receivers of knowledge, but need to beactive researchers, constructors, and communicators of knowledge. Knowledge is no longer handed down fromabove (either from specialists in design, from managers in organizations, or from teachers in courses), but isconstructed collaboratively in the context of design.Figure 3 characterizes the duality and the distributed nature of knowledge: a specific user can learn(specifically: learn in context and on demand) from a computational environment containing knowledge andtools contributed by many stakeholders, but if these users considers themselves designers, they will alsocontribute to the environment (assuming mechanisms are available that allow them to do so with areasonable effort). This perspective illustrates the concepts and need for co-adaptive systems: (1) users learnfrom the systems [Fischer, 1991], (2) users act as innovators, co-developers and designers who adapt andevolve the systems [Lieberman, 2001; Oppermann, 1994], and (3) support for collaborative learning allowsusers to share these adaptations with others [Fischer, 2001].

End-User Modifiability,End-User Programming

Learning on Demand

Figure 3: Duality between Learning and Contributing

Informed participation is based on the fundamental claim mentioned before (see section 2.2) that one of themajor roles of new media is to provide the opportunity and resources for social debate and discussion, ratherthan to merely provide access to predigested information. We cannot really be informed unless weparticipate; and we cannot really participate unless we are informed. By supporting informed participationeffectively, we address the fundamental challenge of how to invent and design a culture in which a l lparticipants in collaborative design processes can express themselves and engage in personally meaningfulactivities.

3.2 Meta-DesignMeta-design [Fischer & Scharff, 2000] is a methodology that characterizes objectives, techniques, andprocesses for creating new media and environments that allow stakeholders to act as designers and contributeto and benefit from the creativity of the group. A fundamental objective of meta-design is to create socio-technical environments that will help all learners and workers to be creative by allowing them to go beyondthe explicitly described functionality of any artifact, to use it in new ways, to evolve it, and to explore itspotential for new processes. Empirical findings [Fischer et al., 2001; Henderson & Kyng, 1991] providerationale for the following meta-design requirements:• Software systems must evolve; they cannot be completely designed prior to use. Design is a process tha t

intertwines problem solving and problem framing [Rittel, 1984]. Software users and designers will notfully determine a system’s desired functionality until that system is put to use, and then its evolutionwill continue with sustained use.


• Software systems must evolve at the hands of the users. End users experience a system’s deficiencies;consequently, they have to play an important role in driving its evolution. Software systems need tocontain mechanisms that allow end-user modification of system functionality [Repenning, 1994].

• Software systems must be designed for evolution. Through our previous research in software design, wehave discovered that systems need to be designed a priori for evolution [Girgensohn, 1992]. Softwarearchitectures need to be developed for software that is designed to evolve [Eisenberg & Fischer, 1994].This is not only true for software, but for other artifacts as well, such as buildings [Brand, 1995]. Brandargues: “Almost no buildings adapt well. They’re designed not to adapt; also budgeted and financed notto, constructed not to, administered not to, maintained not to, regulated and taxed not to, evenremodeled not to. But all buildings (except monuments) adapt anyway, however poorly, because t h eusages in and around them are changing constantly”.

Figure 4 differentiates between design and use stages of an artifact. At design time , system developers byengaging in participatory design processes with users (or their representatives) create environments and tools.In conventional design approaches they create complete systems and make decisions for users for situationalcontexts and for tasks that they can only anticipate. In meta-design approaches they “underdesign” systems[Brand, 1995; Brown & Duguid, 2000] so that unexpected uses of the artifact at use time can be accommodatedby stakeholders. Underdesign is not less work and it is not less demanding, but it is different: it does createsolutions, but it creates environments in which “owners of problems” in situated settings can create solutionsthemselves.

Figure 4: Design and Use Time

Meta-design takes place at design time and is focused on the design of1 . the technical infrastructure providing mechanisms, such as end-user modifiability and end-user

programming, that allow stakeholders to evolve the system at use time;2 . a learning environment and work organization that allows stakeholders to migrate from passive

consumers to end-users, users, and power users (see Figure 2); and3. the socio-technical environment in which stakeholders are recognized and rewarded by their contribution

and can accumulate social capital (see section 6.3. and [Florida, 2002; Putnam, 2000]).Meta-design extends the traditional notion of system design beyond the original development of a system toinclude an ongoing process in which the stakeholders of the system become co-developers. For example, meta-design concepts embedded in Microsoft Word include: (1) users can tailor the system by setting differentparameters as their personal preferences; (2) they can not only use spelling correctors, but they can extend thespelling dictionaries; (3) they can write macros to create new operations; and (4) they can create programs inVisualBasic to extend the functionality of the system.The goal of making systems extensible by users does not imply transferring the responsibility of good systemdesign to the user. Normal users will in general not build tools of the quality a professional designer would. Infact, they are not concerned with the tool, per se, but in doing their work. However, if the tool does not satisfythe needs or the tastes of the users (which they know best) then users should be able to adapt the system


without always requiring the assistance of developers. Gantt and Nardi [Gantt & Nardi, 1992] describe theemergence of “power users” and “local developers” who are technically inclined to perform systemmodifications that other end-users are not inclined to perform. Extensible systems, together with power userswho can perform modifications, enable a process of co-adaptivity between users and system [Mackay, 1990].Users learn to operate a system and adapt to its functionality, and systems are modified to adapt to thepractices of its users.Some of the meta-design principles that we have explored in our own work are:

• support for the seeding, evolutionary growth, and reseeding model, a process model for systems thatevolve as they are used (see section 3.3);

• domain-oriented design environments that take advantage of existing user knowledge and make thefunctionality of the system transparent and accessible so that the computational drudgery required ofthe user can be substantially reduced (see section 4.1); and

• innovative interaction techniques as supported by the Envisionment and Discovery Collaboratory (seesection 4.2) and living computational memories (see section 4.3).

The key challenge for meta-design is the extent to which users can understand a system, learn it, and makechanges. Meta-design must include design for coping with novelty, design for improvisation, and design foradaptation. Making a system extensible introduces additional costs during system development.

3.3 The Seeding, Evolutionary Growth, and Reseeding ModelDespite the best efforts at design time, systems need to evolve at use time to fit new needs, account forchanging tasks, and incorporate new technologies. Designing systems as open, evolving environments istherefore not an option, but a necessity. The seeding, evolutionary growth, and reseeding (SER) model[Fischer et al., 2001] is a descriptive and prescriptive process model for evolving complex environments. I tpostulates that systems that evolve over a sustained time span must continually alternate between periods ofactivity and unplanned evolution, and periods of deliberate (re)structuring and enhancement. The SER modelis based on the observation that design problems in the real world require open systems that users can modifyand evolve (see Figure 4). The SER methodology (by creating a seed instead of a complete system) honorsemergent behavior and it explores interesting new ground between the two extremes of “put-all-the-knowledge-in-at-the-beginning” and “just-provide-an-empty-framework” [Fischer et al., 2001].The SER model (see Figure 5) encourages system designers to conceptualize their activity as meta-design (seesection 3.2) thereby aiming to support users as designers in their own right, rather than as passive consumersof systems and information. Users are seen as informed participants [Arias et al., 1999; Drucker, 1994] whoframe and design solutions to problems, as well as designers in use [Henderson & Kyng, 1991] who modify andextend their systems as needed to suit their purposes.

Figure 5: The Seeding, Evolutionary Growth, Reseeding Process Model


We have explored the feasibility and usefulness of the SER model in the development of domain-orienteddesign environments, organizational memories, courses–as-seeds and course information environments ineducation, and open systems approaches. The evolutions of these systems share common elements, all ofwhich relate to sustained knowledge use and construction in support of informed participation.Seeding. System design methodologies of the past were focused on the objective to build complex informationsystems as “complete” artifacts through the large efforts of a small number of people . Conversely, instead ofattempting to build complete and closed systems, the SER model advocates building seeds that can be evolvedover time through the small contributions of a large number of people.A seed is an initial collection of domain knowledge that is designed to evolve at use time. It is created byenvironment developers and future users to be as complete as possible. However, no information repository canbe truly complete due to the situated and tacit nature of knowledge as well as the constant changes occurringin the environment in which the system is embedded [Suchman, 1987; Winograd & Flores, 1986]. No absoluterequirements exist for the completeness, correctness, or specificity of the information in the seed, but theshortcomings and breakdowns often provoke users to add new information to the seed.Evolutionary Growth. The evolutionary growth phase is one of decentralized evolution as the seed is usedand extended to do work or explore a problem. In this phase, developers are not directly involved because thefocus is on problem framing and problem solving. Instead, the participants have a direct stake in the problemat hand and are designing solutions to problems.During the evolutionary growth phase, the information repository plays two roles simultaneously: (1) i tprovides resources for work (information that has been accumulated from prior use), and (2) it accumulates theproducts of work, as each project contributes new information to the seed. During the evolutionary growthphase, users focus on solving a specific problem and creating problem-specific information rather than oncreating reusable information. As a result, the information added during this phase may not be wellintegrated with the rest of the information in the seed.Reseeding. Reseeding is a deliberate and centralized effort to organize, formalize, and generalizeinformation and artifacts created during the evolutionary growth phase [Shipman & McCall, 1994]. The goalof reseeding is to create an information repository in which useful information can be found, reused, andextended. As in the seeding phase, developers are needed to perform substantial system and informationspace modifications, but users must also participate because only they can judge what information is usefuland what structures will serve their work practices.Reseeding is necessary when evolutionary growth no longer proceeds smoothly. It is an opportunity to assessthe information created in the context of specific projects and activities, and to decide what should beincorporated into a new seed to support the next cycle of evolutionary growth and reseeding. For example,open source software systems [Raymond & Young, 2001] often evolve for some time by adding patches, buteventually a new major version must be created that incorporates the patches in a coherent fashion.The SER model is motivated by how large software systems, such as Emacs, Unix, MS-Word, and MS-Officehave evolved over time. In such systems, users develop new techniques and extend the functionality of thesystem to solve problems that were not anticipated by the systems’ developers (following the observationthat any artifact should be useful in the expected way, but a truly great artifact lends itself to uses t h eoriginal designers never expected).Whereas the people in the above-mentioned development environments are computationally sophisticatedand experienced users, our focus has been on collaborative design in which original environments need to beextended by domain designers (end-users with respect to computational media) who are neither interested innor trained in the (low-level) details of computational environments. Domain designers are more interested intheir design task at hand than in maintaining and evolving knowledge repositories per se. At the same time,important knowledge is produced during daily design activities that should be captured. Rather than expectdesigners to spend extra time and effort to evolve the memory as they design, we provide tools to help themrecord information quickly and without detailed regard for how the information should be integrated withthe seed. Periodically performed reseeding as a collaborative activity between environment developers and


domain designers integrates, restructures, and reorganizes the information accumulated during theevolutionary growth phase.

4 Technology and Media Support for Designer RolesThis section illustrates the conceptual framework articulated in the previous section with specificdevelopments in our research center. It discusses specifically some of the unique abilities of each environmentwith respect to the consumer/designer roles describing the following examples:

• Domain-Oriented Design Environments (DODEs) helping users to interact in their world and makinginformation available on demand;

• Envisionment and Discovery Collaboratory (EDC) empowering stakeholders to articulate theirknowledge and supporting informed participation in face-to-face environments;

• Living Computational Memories managing externalizations thereby sustaining community andproviding support for the SER model.

Conviviality (see section 2.2) is a dimension that sets computers apart from other communication andinformation technologies (e.g., television) that are passive and cannot conform to the users' own tastes andtasks. Passive technologies offer some selective power, but they cannot be extended in ways that the designerof those systems did not directly foresee.Unfortunately, the potential for conviviality exists in many current computer systems only in principle. Manyusers perceive computer systems as unfriendly, uncooperative, and their use as too time consuming; they spendmore time fighting the computer than solving their problems. Many users depend on specialists (“high-techscribes”) for help, and despite the fact that they deal with “soft”ware, they do not experience software as“soft” (i.e., the behavior of a system cannot be changed without reprogramming it substantially). Figure 6classifies media along the consumer/designer spectrum. Broadcast media, like television and magazines,draw strict boundaries between producers of information and consumers, thereby limiting the opportunity forcollaborative interaction. Though these strict boundaries are appropriate for some media in some contexts,they may be very counterproductive and inhibit any creative behavior in other settings. There is afundamental difference between printed and computational media: in print media, a fixed context is createdat design time whereas computational media have the potential that context, form, and behavior at use timecan take advantage of contextual factors known only at use time (see Figure 4). The technical challenge is toallow users to articulate some contextual factors (leading to adaptable systems) or to let the systems infersome of them (leading to adaptive systems) [Fischer, 1993; Oppermann, 1994].

Consumer <----------------------------------------------- ----------------------------->DesignerTV Print Media

Current Computational MediaEnvisioned Computational Media

Figure 6: Technology and Media Support for Consumer and Designer Roles

4.1 Domain-Oriented Design EnvironmentsIf the most important role for computation is to provide people with a powerful medium for expression (inwhich they choose a specific role along the consumer/designer spectrum; see Figure 2), then the mediumshould support them in working on the task, rather than require them to focus their intellectual resources onthe medium itself. When users suffer from a tool mastery burden, their tasks fade to the background while


effort is put toward mastering the tool. To bring tasks to the forefront, computers must become “invisible”[Norman, 1998] allowing users put the majority of their efforts toward interacting with the problem domain,rather than the computer.Domain Oriented Design Environments (DODEs) [Fischer, 1994] are computational systems that supporthuman problem domain interaction (see Figure 8) rather than just human computer interaction. The centraltheoretical vision of DODEs is to provide contextualized support for reflection-in-action [Schön, 1983] indesign activities. DODEs combine an action space with a reflection-space, linked by components such ascritics and argumentation illustrator.

Figure 7: A Domain-Oriented Design Environment for Computer Network Design

Figure 7 shows a DODE for the domain of computer network design. It illustrates the major components (thenumbers refers to the numbered panes in the figure):

1. an argumentation component (serving as the reflection space);2. a palette of building blocks (supporting design by composition);3. a workspace in which a new artifact can be created;4. a specification component (allowing designers to specify priorities); and5. a catalog of existing artifacts (supporting design by modification).


Not shown in the screen image are the critiquing component that increases the “back-talk” of the designsituation [Schön, 1983] by taking advantage of contextual factors known only at use time, and a simulationcomponent that computes the consequences of specific assumptions.DODEs achieve external simplicity with internal complexity . Figure 8 illustrates how the externalsimplicity is achieved: users (being skilled domain workers in some specific domain) have to bridge only ashort conceptual distance from the problems in their respective domain to the design environments for theirrespective domain. This is very different from conventional computational environments where all problemshad to be described in the semantics of the computer or in a general purpose programming language.

ProblemDomains

DesignEnvironments Assembly

Languages

ProgrammingLanguages

ComputerUser

CompilerDeveloper

EnvironmentDeveloper

DomainDesigner

Figure 8: A Layered Architecture Supporting Human Problem Domain Interaction

DODEs have provided a framework for our research about computational support for design by supportingthe development of:

• a software architecture (integrating the components mentioned above) [Fischer, 1994];• substrates with which these components can be developed [Ostwald, 2001; Repenning, 2001]; and• the SER process model (see section 3.3) describing how to build, use, and evolve (1) the general DODE

architecture, (2) specific domain-oriented DODEs, and (3) the individual artifacts developed withina DODE.

4.2 Envisionment and Discovery CollaboratoryDODEs were built during the 1990s, using the computational environments available at the time: personalworkstations. Over time, we became aware of some of the limitations of DODES, such as requiring largeefforts by a few, and providing insufficient support for collaborative design. With new technologies emerging(Smartboards, personal digital assistants, intelligent building blocks, ubiquitous environment, augmentedreality), we started to develop the Envisionment and Discovery Collaboratory (EDC) [Arias et al., 2000],which can be considered a second generation DODE. The EDC helps people to articulate their knowledge andcommunicate with others thereby supporting informed participation. By gathering in face-to-face meetingsaround a computationally enhanced Smartboard, the EDC provides an environment in which users can expresstheir views, learn other views, and coordinate their views. As an engaging forum, the EDC motivatesparticipation, and gives problem owners a voice in framing and solving problems. Figure 9 illustrates oneversion of the EDC supported by Smartboards.


Figure 9: The Envisionment and Discovery Collaboratory

The EDC is an explicit attempt to create an open system (following the process of the SER model) to addresssome of the shortcomings of closed systems. Closed systems (in which the essential functionality isanticipated and designed at design time; see Figure 4) are inadequate to cope with the tacit nature ofknowledge and the situatedness of real-world problems. In our research we have carefully analyzed whysimulation environments such as SimCity [Maxis, 2000] are not be used for real planning and workingenvironments. SimCity supports some superficial kinds of modifications (such as changing the appearance ofbuildings in the city), but most functional aspects of the simulation environment have been determined at theoriginal design time. For example, the only way to reduce crime in a simulated city is to add more policestations. It is impossible to explore other solutions, such as increasing social services. Because thefunctionality of the system was fixed when the system was created, exploring concepts that were notconceived by the system designers is difficult. Because of its closed nature, SimCity may be a good tool forpassive education or entertainment, but it is inadequate for actual city planning tasks as our empiricalinvestigations have demonstrated [Arias et al., 2000]. One vision that drives the EDC is to create an end-userextensible version of Simcity.In the version of the EDC shown in Figure 9, only one user can interact with the game board at a time. This isdue to limitations in the SmartBoard technology and has limited the ability of users to engage in informedparticipation when gathered around the table. Based on the conceptual framework outlined in this paper andon assessments which identified limitations of the SmartBoard technology (such as: no support forsimultaneous actions, moded interactions, lack of computationally enhanced physical building blocks), we areexploring new environments using more sophisticated technology that will make it easier for users to act asdesigners and active contributors.Using a DGT Electronic Chessboard [Eden, 2002], we have created an initial version of a new game boardcalled the Participate-in-the-Action Board (PitA-Board). The underlying technology consists of an 8-by-8grid that can sense the location and identity of 15 distinct transducers. By using multiple grids assembled intandem, we will be able to create versions that are of a more appropriate size for small groups of users. InFigure 10, users interact in parallel with an experimental PitA-Board prototype that supports (1) p a r a l l e linteractions, rather than single-threads of interaction; (2) multiple “points of control” to allow theassociation of various “modes” with various physical objects in the system; and (3) direct sensing of objectsplaced upon the board.


Figure 10: The Participate-in-the-Action (PiTa Board)

The combination of these affordances [Norman, 1993] allows multiple users to interact with the virtualenvironment directly and simultaneously leads to more engaging forms of interaction. Because our interfaceobjects behave more like the domain objects they represent, they support human problem domain interactionby “making the computer invisible” (see Figure 8). In future research, we will investigate in more detailwhether these more direct associations provide an interface that is more accessible to naïve users andprovides a medium that supports a more natural interaction with the underlying simulation medium [Eden,2002].

4.3 Living Computational MemoriesLiving computational memories [Terveen et al., 1995] manage the information content of evolving systemsdiscussed in this article. They can stand alone, but they can also serve as components in DODEs and the EDC.Living computational repositories developed with the SER model can overcome the fundamental limitationswhich closed systems will have when applied to real world problems. We have investigated livingcomputational memories in a variety of different settings, including: (1) argumentation spaces in DODEs andthe EDC (see sections 4.1 and 4.2); (2) conceptual spaces (glossaries) associated with the work of researchgroups [Fischer & Ostwald, 2001]; (3) course information environments for courses taught in universities[dePaula et al., 2001]; and (4) organizational memories supporting knowledge management [Fischer &Ostwald, 2001]. To support users as effectively as possible, we have designed and implemented a number ofdifferent substrates including Swikis [Guzdial & Jocken, 2001; Scharff, 2002], Dynasite [Ostwald, 2001], andlivingOM [Ostwald, 2002].Design cultures in which people engage in informed participation lead to new forms of knowledge creation,integration, and dissemination [Fischer & Ostwald, 2001] (as further discussed in section 5.2). A principalchallenge of informed participation is to capture a significant portion of the knowledge generated by workdone within a community. Experiences with organizational memories and collaborative work have exposedtwo barriers to capturing information: (1) individuals must perceive a direct benefit in contributing toorganizational memory that is large enough to outweigh the effort [Grudin, 1994]; and (2) the effort requiredto contribute to organizational memory must be minimal so it will not interfere with getting the real workdone [Carroll & Rosson, 1987].


Externalizations [Bruner, 1996] (created for example by the stakeholders in a problem framing and solvingsession supported by the EDC; see Figure 9) have the following essential roles to support informedparticipation in a designer culture:

• they assist in the translation of vague mental conceptualizations of ideas into more concreterepresentations. They require the expression of ideas in an explicit form, and in this process, as wellas the end result, may reveal ideas and assumptions that beforehand were only tacit [Polanyi, 1966];

• they provide a means for stakeholders to interact with, react to, negotiate around, and build uponideas. Such a “conversation with the materials” of the design problem [Schön, 1983] is a crucial modeof design that can inspire new and creative ideas; and

• they focus discussions upon relevant aspects of the framing and understanding of the problem beingstudied, thereby providing a concrete grounding and a common language among stakeholders.

Living computational memories serve a member community but they are also (at least partially) open to“outsiders”. They must serve the spectrum of users, and support migration among different roles rather thanpigeon-hole users in whatever role. The different consumer/designer roles (see Figure 2) in the context ofliving computational memories are:• Consumers — come from outside of the member community visiting the memory but they do not use it as

part of their day-to-day activities; this group includes passive consumers who merely view contents andactive consumers who might add a comment or sign a guest book.

• Users — are the members of the community, who use the memory in their day-to-day activities. Theycontribute to the memory, but not all contribute on the same level: (1) end-users add content to the memory(for example, they maintain their personal page and contribute their work to the system, as well ascommenting on the work of others); (2) power-users add contents to the memories just as end-users do, butin addition they are interested (or become interested over time) in how the system works and how theycan modify it. Power users can emerge either coming from the user community (learning over time moretechnical knowledge) or from the developer community (learning over time more application knowledge).Either way, they have a mix of knowledge that includes eventually both domain knowledge and toolknowledge.

• Developers — are specialists in the technical aspects of the memories and the underlyingimplementation details. Developers in general have limited knowledge about the users’ domain. Theyhave the technical knowledge to make major changes to the system, but must rely on users to know whatchanges to make.

• Meta-designers — are developers who are concerned to create the social and technical context that willenable users to be active and creative and they create mechanisms that will put owners of problems incharge. They must know about both the application domain and technology in depth. They areresponsible to design basic schema and mechanisms that are implemented by the developer, extended bythe power-user, customized by the end-user, and accessed by the consumer.

5 The Ubiquity of the Consumer / Designer SpectrumThe previous section illustrated the conceptual framework articulated in section 3 of the consumer/designerdistinction with specific developments in our research center. The consumer/designer distinction providesimportant requirements for these developments and at the same time, these developments help to deepen ourunderstanding of the consumer/designer perspective. This section briefly discusses the consumer/designerperspective as a fundamental aspect of human behavior in three specific different application domains: (1)architecture, (2) open source, and (3) learning and education.


5.1 ArchitectureArchitecture has served as the prime example for the argument of many design methodologists (e.g., [Rittel,1984; Schön, 1983] who demonstrate with their work that the design of complex systems requires theintegration of problem framing and problem solving. New requirements emerge during development becausethey cannot be identified until portions of the system have been designed and implemented. The conceptualstructures underlying complex systems are too complicated to be specified accurately in advance and toocomplex to be built faultlessly. Problem framing and problem solving have to co-evolve requiring the ownersof the problems to be present in the development.The attempt to build complete systems at design time (see Figure 4) implies that all the design intelligencegets forced to the earliest part of the building process, when everyone knows the least about what is reallyneeded [Brand, 1995]. Without customizability and extensibility built into the initial design, users have nopossibility to react to breakdowns [Fischer, 1994]. Alexander calls a design culture in which owners ofproblems can react to breakdown unselfconscious [Alexander, 1964]. The strength of an unselfconscious cultureof design is that the actual use context is known at the time when breakdowns occur rather than anticipatedat design time.Architecture also serves as a good example domain to understand the pitfalls associated with evolutionarydesign. The Oregon Experiment [Alexander et al., 1975] (a housing experiment at the University of Oregoninstantiating the concept of end-user-driven evolution) serves as an interesting case study that end-user-driven evolution is no guarantee for success. The analysis of its limited success indicated two major reasons: (1)there was a lack of continuity over time, and (2) professional developers and users did not collaborate, sothere was a lack of synergy.These findings have led us in part to postulate the need for a reseeding phase (making evolutionarydevelopment more sustainable), in which developers and users engage in intense collaborations possiblyredirecting the direction of the evolutionary growth. With design rationale captured, communicationenhanced, and end-user modifiability supported, developers have a rich source of information to evolve thesystem in the way users really need it.

5.2 Open Source: A Success Model of Collaborative Design in a Designer Culture“Linux was the first project to make a conscious and successful effort

to use the entire world as a talent pool” — Raymond, E. S. & Young, B. (2001)

Open source development [Raymond & Young, 2001] is an activity where a community of software developerscollaboratively constructs systems to help solve problems of shared interest and for mutual benefit.Understanding open source as a process of collaborative design [Scharff, 2002] highlights the socio-technicalaspects of open source software where the participation of a community is vital to its success, and where thefinal product emerges out of the contributions of the entire community. Development in the open sourcecommunity has been characterized by principles such as “(1) in gift cultures, social status is determined not b ywhat you control but by what you give away, (2) prestige is a good way to attract attention and cooperationfrom others, and (3) utilization is the sincerest form of flattery.” Powerful tools and environments such as theLinux operating system and the Apache Web server have become both useful and reliable because of theevolutionary contributions of a large community of motivated developers. They provide an interestingexistence proof that reliable, useful, and complex systems can be built in a decentralized “Bazaar style” bymany rather than in a centralized, “Cathedral style” by a few [Resnick, 1994].A defining characteristic of open source software is that the source code for that software can be obtained andmodified by anyone who wishes to do so. The ability to change source code is an enabling condition forcollaborative construction of software because it allows software developers to make changes to the behaviorof the software. This changes software from a fixed entity that is produced and controlled by a closed group ofdesigners to an open effort where a community can collaboratively design following the framework providedby the SER model (see section 3.3). Open source software provides technical and legal mechanisms allowingusers who would otherwise be passive consumers to become active contributors. While this is a necessarycondition, it is by no means a sufficient condition: beyond having the technical skill to change the software,


engaging in modification requires the time, inclination, and motivation to do so. Using open source as a successmodel for collaborative design [Scharff, 2002], we have identified the following principles:1. making changes must seem possible: users should not be intimidated and should not have the impressions

that they are incapable of making changes; the more users become convinced that changes are not as hardas they think they are, the more they may be willing to participate;

2. changes must be technically feasible: if a system is closed, then users cannot make any changes; as anecessary prerequisite, there needs to be possibilities for extension (created by a meta-designmethodology, see section 3.2);

3 . benefits must be perceived: contributors have to believe that what they get in return justifies theinvestment they make. The benefits perceived may vary and can include: professional benefits (helpingfor one’s own work), social benefits (increased status in a community, possibilities for jobs), and personalbenefits (engaging in fun activities);

4. open source environments must support tasks that people engage in: the best open source system will notsucceed if it is focused on activities that people do rarely or consider of marginal value; and

5. low barriers must exist to sharing changes: if sharing is awkward, it creates an unnecessary burden thatparticipants may feel unwilling to overcome. Evolutionary growth is greatly accelerated in systems inwhich participants can share changes and keep track of multiple versions easily.

5.3 Learning and EducationLearning from breakdowns [Fischer, 1994; Schön, 1983] is an effective way to learn by trying to do somethingand getting stuck. We can make mistakes only when we do something — not when we engage in passiveobservation. Learning by doing is in sharp contrast to one of the most frequently practiced but mostimpoverished paradigms of education (based on the assumption that learners are consumers of knowledge): asetting where “a single, all-knowing teacher tells or shows presumably unknowing learners something theypresumably know nothing about” [Bruner, 1996]. This model of education (which is widely practiced in oureducational institutions) has led critics such as Illich [Illich, 1971] to the claim that our schools anduniversities are the “reproductive organs of a consumer society” and “people who are hooked on teaching a r econditioned to be customers for everything else.” As an alternative, we should reconceptualize and reinventclassrooms and work environments as places where (1) communities of mutual learners act simultaneously aslearners and as active contributors, (2) peer-to-peer learning is supported and teachers act as “guides on theside” rather than as “sages on the stage”, and (3) where courses are considered as seeds rather than finishedproducts [dePaula et al., 2001]. Such models of learning and education will require innovative computationalenvironments that will share many of the requirements and challenges articulated in this article. Theargument that consumerism is a mindset [Fischer, 1999] implies that there is no evidence that a “big switch”theory will succeed, meaning that a student who was educated as a passive consumer will suddenly switch tobeing an active contributor. If the world of working and living requires a designer perspective (by relying oncollaboration, creativity, definition and framing of problems, dealing with uncertainty, change, anddistributed cognition), then our schools and universities need to prepare learners to be designers rather thanconsumers to have meaningful and productive lives.The approach presented in this paper is in line with characterizations of post-tayloristic work environments[Brown & Duguid, 2000] attempting to increase the creativity of their workers by finding new ways toconceptualize working and learning. Some of the key dimensions of this perspective are illustrated in Table 2.


Table 2: Traditional versus New Models of Working and Learning in Organizations

traditional new

paradigm knowledge transmission knowledge construction

learning classroom, curriculum driven on demand, in context

tasks system driven (canonical) user/task driven

social structures individuals in hierarchical structures collaborative in flat structures

work style standardize improvise

information spaces closed, static open, dynamic

breakdowns error to be avoided opportunity for innovation and learning

communication top-down peer-to-peer

Our work in courses with students over the years has provided some encouragement that there is interestamong some of the students to act as designers. For example: in courses focused on integrating the web intotheir activities, we failed to entice students to spend a significant amount of time browsing the web.Although the students spent some time looking at suggested sites, they were not too interested in spending alot of time browsing. They had little patience for technical problems like the network being slow, or down,and quickly become frustrated if they could not find the information they were seeking. This attitudechanged significantly when the students started creating their own sites. We noticed that once they got overthe initial learning curve for web authoring tools they were using, they had much more patience for thetechnology especially when they were able to see and could show to others the pages that they had createdon the web. To support this migration path from consumer to designer [Burton et al., 1984], it is important tha tthe difficulty of getting students to learn enough of the technology to start creating their own sites is notunderestimated. This is especially true for students with limited technical experience and interest (who willstumble over file formats, HTML tags, and protection codes). The learning efforts and the design efforts needto be minimized by having powerful web authoring tools [Guzdial & Jocken, 2001; Ostwald, 2002] and byshielding the students (use scaffolding techniques and wizards) from the added difficulties of setting up siteson servers.

6 AssessmentThe basic theme addressed by this article is to explore the fundamental challenge for computational mediato contribute to the invention and design of cultures in which humans can express themselves and engage inpersonally meaningful activities. The system developments described in section 4 were driven by this andrelated objectives including: (1) how we can support skilled domain workers who are neither novices nor naiveusers, but who are interested in their work and who see the computer as a means rather than as an end; and (2)how we can create co-adaptive environments, in which users change, because they learn, and in whichsystems change, because users become co-developers and active contributors. While environments developedwithin a meta-design framework and providing support for the SER model are necessary, they are notsufficient to create a designer culture. Claims made more than a decade ago such as “technology will becomeso flexible that users will be able to customize it ever-more precisely to meet their particular needs — aprocess that might be termed ‘mass customization’” based on “providing people with easy-to-useprogramming tools so they can customize the information systems and computer applications that they workwith” [Brown, 1991] have at best been only partially a reality. This section will assess the claims and hopesfrom a number of different dimensions.


6.1 Technology AssessmentThe computational environments described in this article were developed to give owners of problems a voiceby simultaneously transcending the limitations of closed systems and honoring the knowledge of domainworkers coming from different communities of practice. Their developments were driven by the hypothesisthat many of the distinctions between designers and users should become blurred and that all humans canpotentially become designers in case they find the tasks personally meaningful enough.As argued earlier, there is ample evidence that closed systems do not work, including the limitations ofclosed expert systems [Winograd & Flores, 1986], closed simulations such as Simcity [Arias et al., 2000], andclosed computational memories [Fischer & Ostwald, 2001; Terveen et al., 1995]. Because users experiencebreakdowns and insufficiencies of an environment in their work, they should be able to report, react to, andresolve those problems. Mechanisms which empower owners of problems to change, tailor, and modify theirenvironments are a cornerstone of extensible and evolvable systems. At the core of our approach toevolutionary design lies the ability of owners of problems to make significant changes to systemfunctionality, and to share those modifications within a community of designers. The types of changes tha tmust occur during the evolutionary growth of a system go beyond the setting of predefined parameters orpreferences and include the ability to alter system behavior in non-trivial ways.

Lessons learned from our work show that in order to support the development of the designer culture needed toaddress the challenges of open systems, activities at design time and use time (see Figure 4) need to bereconceptualized. The experience which we have gained with developing systems from a meta-designperspective has indicated that a substantial part of the system needs to be dedicated to components,structures, and mechanisms to support users acting as designers. The extensibility component of one of ourdomain-oriented design environments (see section 4.1) contains more than 60 percent of the program code of theoverall system [Girgensohn, 1992] indicating that meta-design is a non-trivial task. Henderson and Kyng[Henderson & Kyng, 1991] argue that design for extensibility is still advantageous because the resources savedin the initial development by ignoring extensibility will be spent several times over during the system'slifetime. Unless extensibility and evolvability are considered as a necessity rather than a luxury, thepossibilities at use time will be limited and the efforts required too large.

6.2 Utility = Value / Effort“Humans want things as easy as possible for them. The reason we are a consumer society is

because that’s what we want to be.” — a student in one of our courses

Building systems that supports users to act as designers and not just as consumers are often less successful thanthe meta-designers have hoped for. Environments inviting informed participation are created with manygood intentions at design time but the participation and contributions that actually occur often do not live upto the expectations, a finding which can be characterized by “build it—and they will not come” [Smith &Farquhar, 2000]. Analyses of these failures of adoption and sustained use of systems can be seen in manydomains, including groupware applications, organizational memories, and knowledge management systems.The missing contributions can be attributed to many factors, including lack of institutional buy-in of proposedtechnologies, insufficient involvement of users during development (ignoring principles of participatorydesign), and lack of attention to the dimensions discussed in this paper. We will analyze these barriers usingthe equation

“utility = value / effort”

meaning that people will decide on the worthiness of doing something (utility) by relating the (perceived)value of an activity to the (perceived) effort of doing it.In many design activities, the question to be asked is: “who puts in the effort?”, and there exists often animportant trade-off: more effort at design time results in smaller efforts at use time. Major efforts at designtime are needed to create DODEs and EDCs, to seed computational memories with substantial content, and tocreate the meta-design structures that will empower users at use time to engage in informed participation andgreatly reduce their efforts. Value consideration at design time can lead to “better” systems that (1) more


people will buy (economic incentive) or (2) more people will use (social capital). Value at use time is greatlyinfluenced by allowing people to engage in personally meaningful tasks.People are willing to spend considerable efforts on things that are important to them and the value dimensionfor truly personal meaningful task will be more important than the effort dimension. Learning to drive anautomobile is not an easy task, but almost all people learn it because they associate a high personal valuewith it. A mother who learns that her child is autistic is probably more motivated to join a social network ofother caregivers as can be inferred from the following statement (quoted in autism articles in Time Magazine,May 6, 2002): “When I stopped crying, I went to my office and called everyone I had ever met who was in anyway connected to the world of special-need kids. We made a lot of mistakes before finding the perfect matchfor our child”. Despite small efforts to contribute to computational memories, we have found that people willnot do it if they personally consider the value to be at best marginal.

6.3 Social Capital“I have better things to do with my life than write Word macros.”

— a researcher in our center

Social capital (e.g., in the work of [Putnam, 2000]) means reciprocity — if you do something for someone, theyare more likely to do something for you — and it is based on mutual respect and being a good citizen. Thegeneral decline in social capital in society observed by Putnam is attributable to several factors, but he arguesone of them is that television and other mass media take too much of many people’s time. This will reducepeople’s active pursuits leading to a shift from a “doing culture” to a “watching culture” [Florida, 2002] (andincrease the number of “couch potatoes” in our societies).The designer culture envisioned in this paper relies on people who are willing to contribute because a problemor an activity is personally meaningful to them, and/or their contribution helps to come up with a bettersolution. The incentive for the contribution is rarely monetary. Recommmender systems [Terveen & Hill, 2001]are a good example relying on this behavior: the recommenders get rewarded by recognition and feedback andthe users will be satisfied if they receive recommendations that are relevant and interesting.Social capital is of critical importance to motivate people to share their individual contributions,modifications and extensions to evolving systems and computational memories with other users. A designerculture relies on active contributors who are knowledgeable in their respective fields. In computationalenvironments they must also have the technical competence to articulate their knowledge. While these twoaspects are necessary, they are not sufficient. People must be motivated and rewarded for investing time andeffort to become knowledgeable enough to act as designers. These rewards may range from (1) feeling in control(i.e., independent from “high-tech scribes”), (2) being able to solve or contribute to the solution of a problem,(3) a passion to master a tool in greater depth, (4) an ego-satisfying contribution to a group, and (5) goodcitizenship in a community. A designer culture emphasizes the social character of working and learning “inwhich people act as resources for one another, rather just as one another’s information provider” [Brown &Duguid, 2000].In a design culture, skilled domain workers will see providing additional information as part of their workrather than as an extra task. A first step in this direction is to identify and encourage members of thecommunity who are interested and inclined to become power-users [Nardi, 1993]. These users are more willingto learn new mechanisms and can assume a leadership role within the community. The emergence of such rolesis another indication of community formation and is an essential aspect of social capital. The design of oursystems (see section 4) has been driven by the design objective that serious learning and active contributing(see Figure 3) does not have to be unpleasant but can be personally meaningful, empowering, engaging, and fun.


6.4 Trade-offs in a “Do-It-Yourself Society”“You're not going to make a Hollywood feature with iMovie,

but you can make some pretty cool home movies from the holidays.“— a researcher in our center

This article advocates the desirability of a designer culture for tasks and activities that people considerpersonally meaningful, which they enjoy doing, and in which they want to be independent of high-techscribes or. A “Do-It-Yourself Society” is often associated with these goals: creating your own artifactsinstead of buying of-the-shelf products (see Figure 1).There has been another shift taking place, starting with self-service restaurants and self-service gas stationsa few decades ago, and this trend has been greatly accelerated over the last 10 years. Through modern tools(including electronic commerce supported by the Web), humans are empowered to do many tasks themselvesthat were done previously by skilled domain workers serving as agents and intermediaries [Brown & Duguid,2000]. While this shift provides power, freedom, and control to customers (e.g., banking can be done at anytime of the day with ATMs, and from any location with the Web), it has lead also to some less desirableconsequences. People may consider some of these tasks personally not very meaningful and therefore would bemore than content with a consumer role. Aside from simple tasks that require a small or no learning effort,customers lack the experience the professionals have acquired and maintained through daily use of systems,and the broad background knowledge to do these tasks efficiently and effectively. The tools used to do thesetasks — banking, travel reservations, buying airline tickets, checking out groceries at the supermarket — arecore technologies for the professionals, but occasional technologies for the customers. This will put a new,substantial burden on customers rather than having skilled domain workers doing these tasks.

6.5 MindsetsThis article is based on the hypotheses (1) that cultures are substantially defined by their media and theirtools for thinking, working, learning, and collaborating, (2) that a large number of new media are designed tosee humans only as consumers, and (3) that people, particularly young people in our educational institutions,form mindsets based on their exposure to specific media [Fischer, 1999].

The current mindset about learning, teaching, and education is dominated by a view in which teaching isoften fitted “into a mold in which a single, presumably omniscient teacher explicitly tells or showspresumably unknowing learners something they presumably know nothing about” [Bruner, 1996]. A criticalchallenge is a reformulation and reconceptualization of this impoverished and misleading conception.Learning should not take place in a separate phase and in a separate place, but should be integrated intopeople’s lives allowing them to construct solutions to their own problems. As they experience breakdowns indoing so, they should be able to learn on demand by gaining access to directly relevant information. The directusefulness of new knowledge for actual problem situations greatly improves the motivation to learn the newmaterial because the time and effort invested in learning are immediately worthwhile for the task at hand— not merely for some putative long-term gain. As argued before (see section 2.2): to create designer mindsets,learning cannot be restricted to finding knowledge that is “out there”. Rather than serving as the“reproductive organ of a consumer society” [Illich, 1971], educational institutions must cultivate thedevelopment of a “designer mindset” by creating habits and tools that help people become empowered andwilling to actively contribute to the design of their lives and communities.

Beyond supporting contributions from individual designers, we need to find ways to build a culture andmindset of sharing, supported by effective technologies and sustained by personal motivation to occasionallywork for the benefit of groups and communities. This includes finding ways for people to see work done for thebenefits of others being "on-task", rather than as extra work for which there is no recognition and no reward.If learning can become a new form of labor [Zuboff, 1988], then why can the same objective not be associatedwith sharing?


6.6 Cross-Cultural PerspectivesI have written this paper coming from a specific cultural background: an embedding in European / Americanculture in which individualism may be more valued than collectivism [John-Steiner, 2000]. There are othercultural backgrounds in which people feel more comfortable being guided by a sage (i.e., by listening to ateacher, by accepting the opinion articulated or the artifact created by an expert). There is growing evidencethat many computational artifacts (as they take more cultural themes into account in areas such asparticipatory design, computer-supported cooperative work, and computer-supported collaborative learning)will require more than simple translation efforts when ideas and systems are moved across culturalboundaries. Some quotes from Chinese and Japanese students taking some of my courses at the University ofColorado, Boulder, provide evidence of these cultural differences:

• “I have no designer experience in school education that I can remember. I was astonished by t h eheated arguments in the USA's classroom when I first took a course at CU. Sometimes students act a steachers. They speak out their minds and opinions loudly.”

• “In China, students are taught to respect instructors, which is good, however, the students are onlysupposed to be listeners and followers, and students and instructors are never at the same l ev e l .Therefore, there's no way for students and instructors to be co-learners and co-designers. There's an o l dChinese saying that youngsters should not point out elders' faults. Teachers are superior.”

I believe that we all become more aware of our own cultures as we encounter, reflect and discuss differentcultures—an effort that I would consider an important element of the “designer culture” articulated in thispaper.

7 ConclusionsPeter Drucker argued that “there is nothing so useless as doing efficiently that which should not be done atall.” Adding new media and new technologies to existing practices will not change the consumer mindsets oflearners and workers. We need to explore new computational media based on fundamental aspects of how wethink, create, work, learn, and collaborate. It simply is not good enough to spend money on new technologiesand then to use it in old ways. New tools should not only help people to do known cognitive tasks more easily,but they should lead to fundamental alterations in the way problems are solved.

In a designer culture breakdowns will be seen as opportunities rather than as things to be avoided; teacherswill understand their roles not only as truth-tellers and oracles, but as coaches, facilitators, and mentors; andknowledge will not be presented as a commodity to be acquired or delivered, but as a human struggle tounderstand and as a source to deal with personally meaningful problems. The future of how we live, think,create, work, learn, and collaborate is not out there to be “discovered”— it has to be invented and designed.This design should not be dominated or solely determined by technocrats or Hollywood, but requires theinterdisciplinary collaboration among different social groups. It is of critical importance that the human andsocial sciences are not content with a spectator and Cassandra role in this process. Computational media offerthe possibilities and the potential to allow people to express themselves and to create personally meaningfulenvironments. These possibilities should not be accessible only to a small group of high-tech scribes, butshould provide an opportunity for all interested individuals and groups. The socio-technical design ofcomputational environments requires the social inclusion and active participation of the users as activecontributors, rather than the more typical situation in which the designers are far removed from the dailytasks and activities of the people who use the environments.Computational media can have the same fundamental impact on our individual lives and our societies asreading and writing had to move us from oral to literal societies. The true contribution of computationalmedia might be to allow all of us to take on, or incrementally grow into a designer role in areas that weconsider personally meaningful and important so we do not mind additional efforts.


8 AcknowledgmentsThe author would like to thank the members of the Center for LifeLong Learning & Design (L3D), who havemade major contributions to the conceptual framework and systems described in this paper. A special thankyou goes to: (1) Jonathan Ostwald who has helped me to create many of the illustrations used in the paperand who has provided critical feedback to an earlier version, (2) Ernie Arias and Hal Eden who are the majordevelopers of the Envisionment and Discovery Collaboratory, and (3) to Eric Scharff and Yunwen Ye whocollaborated with me on themes focused on social capital, open source communities and software reuse. BlairMcMaster (University of Canterbury, New Zealand) provided valuable feedback on an earlier draft.The research described has benefited substantially from major initiatives at the University of Colorado atBoulder including: the Alliance for Technology, Learning and Society; the Integrated Teaching and LearningLaboratory; and the Discovery Learning Initiative. Details about these initiatives can be found at :http://www.colorado.edu/ .The research was supported by (1) the National Science Foundation, Grants (a) REC-0106976 “SocialCreativity and Meta-Design in Lifelong Learning Communities”, and (b) CCR-0204277 “A Social-TechnicalApproach to the Evolutionary Construction of Reusable Software Component Repositories”; (2) SRA KeyTechnology Laboratory, Inc., Tokyo, Japan; and (3) the Coleman Initiative, San Jose, CA.

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